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Normalization (image processing) In image processing, normalization is a process that changes the range of pixel intensity values. Applications include photographs with poor contrast due to glare, for example. Normalization is sometimes called contrast stretching or histogram stretching. In more general fields of data processing, such as ...
Histogram equalization accomplishes this by effectively spreading out the highly populated intensity values which are used to degrade image contrast. The method is useful in images with backgrounds and foregrounds that are both bright or both dark. In particular, the method can lead to better views of bone structure in x-ray images, and to ...
Image scaling. In computer graphics and digital imaging, image scaling refers to the resizing of a digital image. In video technology, the magnification of digital material is known as upscaling or resolution enhancement. When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric ...
Transformation matrix. In linear algebra, linear transformations can be represented by matrices. If is a linear transformation mapping to and is a column vector with entries, then for some matrix , called the transformation matrix of . [citation needed] Note that has rows and columns, whereas the transformation is from to .
Feature detection on 1-D time domain data using phase stretch transform. Phase stretch transform (PST) is a computational approach to signal and image processing. One of its utilities is for feature detection and classification. [1][2] PST is related to time stretch dispersive Fourier transform. [3] It transforms the image by emulating ...
Anamorphic format is the cinematography technique of shooting a widescreen picture on standard 35 mm film or other visual recording media with a non-widescreen native aspect ratio. It also refers to the projection format in which a distorted image is "stretched" by an anamorphic projection lens to recreate the original aspect ratio on the ...
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